README.md

# What is this tool?

Let's all be frank, root sucks and the root file format is horrible.
It's among humanities worst pieces of software. With this small tool I hope to fix
the damage that was done, at least a little, by converting root files into
native Python formats.


It's using [Numpy](https://numpy.org) and a library called [Uproot](https://github.com/scikit-hep/uproot5)
to read and process these damn root files. So far it is specialist for one task
and I will have to work on it to make it actually viable for more use cases. That task
is to extract PXD data from Belle 2 data files.


## How to use this?

This is a single class, that needs to be instantiated, it doesn't take any arguments.
Just import it like this:

> from rootable import Rootable

Then you can create an instance:

> loadFromRoot = Rootable()

and load the root file and all the data:

> loadFromRoot.loadData('/root-files/slow_pions_2.root')
> loadFromRoot.getClusters()
> loadFromRoot.genCoordisnate()
> loadFromRoot.getLayers()
> loadFromRoot.getMatrices()
> loadFromRoot.getMCData()

This commands don't have any return value, but instead work in-place.
Then all data is stored inside the object as dict:

> loadFromRoot.data

Here follows a list of keywords contained in the dict:

- cluster data:
    - 'eventNumbers'
    - 'clsCharge'
    - 'seedCharge'
    - 'clsSize'
    - 'uSize'
    - 'vSize'
    - 'uPosition'
    - 'vPosition'
    - 'sensorID'
- coordinates:
    - 'xPosition'
    - 'yPosition'
    - 'zPosition'
- layers:
    - 'layers'
    - 'ladder'
- matrices:
    - 'cluster'
- Monte Carlo data:
    - 'momentumX'
    - 'momentumY'
    - 'momentumZ'
    - 'pdg'
    - 'clsNumber'

Since the class is subscriptable one can access every element directly using the keywords
like this:

> loadFromRoot['eventNumber']

or

> loadFromRoot[0]

will return either the array containing the event numbers of the first entry of every
array contained in the classes dict.

And finally you can convert the dict into a structured Numpy array by simply writing:

> loadFromRoot.loadFromRoot()

This last command returns a Numpy array. From there the user can save it using
Numpys build-in functions, convert it to Pandas or use it in any way that is
compatible with Numpy.


## Installation

You will need to the wheel and setuptools packages of python in order to install

Download the repo, navigate in the terminal to the folder and run the following script:

> python3 setup.py bdist_wheel sdist

and then:

> pip3 install .